The Scaled Growth team, part of the Monetization Product organization, builds the products that enable small and medium-sized businesses to advertise and grow on TikTok.
We solve complex challenges in simplifying campaign creation, automating optimization, and delivering effective guidance at scale, for advertisers with diverse needs and limited resources.
The quality of those solutions directly influences advertiser success, retention, and access to sustainable growth.
You will help democratize digital advertising, on work with measurable impact for businesses worldwide.
About the Team and Role
TikTok's Product-Led-Growth team is focused on helping businesses of all sizes succeed through TikTok's advertising platform.
Our mission is to drive scalable advertiser growth by building product experiences that make it easier, faster, and more effective for customers to onboard, activate, and grow their business.
As part of a global organization, the PLG team works at the intersection of product strategy, growth, data, and user experience.
We are looking for an AI Growth Product Lead to own three connected product areas: a Paid Ads Agent, GEO audit and optimization automation, and a unified Growth Marketing Platform.
You will define the product strategy and lead execution across AI, advertising, attribution, creative production, lifecycle engagement, and platform experience.
You will partner closely with Engineering, AI/ML, Data Science, Design, Marketing, Sales, Operations, Privacy, and Legal.
Responsibilities
Product Strategy & Controls
- Own the vision, roadmap, and success metrics for the AI growth portfolio, translating customer needs and growth goals into scalable products, platform capabilities, and experiments.
- Define clear boundaries between autonomous execution, human review, and manual control, with appropriate permissions, evaluation, explainability, audit, rollback, and escalation mechanisms.
Growth Agents & AI Automation
- Build agents that plan, launch, monitor, diagnose, and optimize paid campaigns, including audience, budget, bidding, creative, pacing, and performance recommendations.
- Develop GEO capabilities that measure brand visibility and answer quality, identify content gaps, and automate prompt auditing, content optimization, publishing, and impact measurement using first-party and external signals.
Growth Marketing Platform
- Unify identity, campaign orchestration, creative production, activation, attribution, experimentation, reporting, and lifecycle engagement across paid, owned, and organic channels.
- Enable reusable APIs, integrations, and workflow templates for internal and external activation, including privacy-aware attribution and incrementality measurement.
- Advance AI-powered creative generation, localization, quality review, performance learning, and automated lifecycle engagement while improving reliability, latency, data freshness, and user experience.
AI-Native Organization Enablement
- Define the AI-native operating model and prioritize high-value workflows for augmentation, automation, and agent-led execution across Product, Growth, Marketing, Sales, and Operations.
- Build reusable enablement infrastructure—including approved tools, data connectors, templates, evaluation harnesses, and shared agent components—and redesign workflows with clear human-in-the-loop controls.
- Drive adoption through training, playbooks, office hours, and AI champions;
establish privacy, security, model-risk, and audit governance, and measure impact through usage, cycle time, quality, automation coverage, cost, and decision velocity.
Leadership & Execution
- Use research, behavioral data, experiments, and failure analysis to guide decisions and track growth impact, efficiency, adoption, reliability, task quality, and user satisfaction.
- Align senior stakeholders, resolve roadmap trade-offs, lead distributed cross-functional teams, and stay hands-on with prototypes, data, agent testing, customers, and launch reviews.
Success Measures:
- Incremental acquisition, conversion, retention, and revenue impact.
- Improved marketing efficiency and reduced manual operating cost.
- Adoption and repeat usage across agent, GEO, creative, attribution, activation, and lifecycle capabilities.
- Higher task success and automation coverage with fewer high-severity failures.
- Strong platform reliability, performance, data quality, and user satisfaction.